Zhuang Liu

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	Visi	Nuo 2019
Šaltiniai	70560	66688
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Kilian WeinbergerCornell UniversityPatvirtintas el. paštas cornell.edu
Laurens van der MaatenDistinguished Research Scientist, Llama Team, Meta AIPatvirtintas el. paštas meta.com
Trevor DarrellProfessor of Computer Science, U.C. BerkeleyPatvirtintas el. paštas eecs.berkeley.edu
Zhiqiang ShenAssistant Professor at Mohamed bin Zayed University of Artificial IntelligencePatvirtintas el. paštas mbzuai.ac.ae
Saining XieAssistant Professor at the Courant Institute, New York UniversityPatvirtintas el. paštas nyu.edu
Jianguo LiDirector, Ant GroupPatvirtintas el. paštas antgroup.com
Christoph FeichtenhoferMeta, FAIRPatvirtintas el. paštas fb.com
Chao-Yuan WuWorld LabsPatvirtintas el. paštas meta.com
Hanzi MaoResearch Scientist, NvidiaPatvirtintas el. paštas nvidia.com
Yu SunPostdoc, Stanford UniversityPatvirtintas el. paštas cs.stanford.edu
Xiaolong WangAssistant Professor, UC San DiegoPatvirtintas el. paštas ucsd.edu
Mingjie SunCarnegie Mellon UniversityPatvirtintas el. paštas cs.cmu.edu
Tinghui ZhouPhD student, UC BerkeleyPatvirtintas el. paštas berkeley.edu
Bingyi KangResearch Scientist @ TikTokPatvirtintas el. paštas sea.com
Xinlei ChenFAIR, MetaPatvirtintas el. paštas meta.com
Rohit GirdharResearch Scientist, GenAI, MetaPatvirtintas el. paštas fb.com
Yurong ChenSr. Principal AI Scientist / Research Director, Intel Labs ChinaPatvirtintas el. paštas intel.com
Moritz HardtMax Planck Institute for Intelligent SystemsPatvirtintas el. paštas is.mpg.de
Alexei A. EfrosDept. of Electrical Engineering and Computer Sciences, UC BerkeleyPatvirtintas el. paštas eecs.berkeley.edu
Ronghang HuResearch Scientist, AI at MetaPatvirtintas el. paštas meta.com

Stebėti

Zhuang Liu

Research Scientist, FAIR, Meta

Patvirtintas el. paštas berkeley.edu - Pagrindinis puslapis

Deep Learning Neural Networks Computer Vision Machine Learning


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Densely Connected Convolutional Networks Z Liu, G Huang, L Maaten, KQ Weinberger Computer Vision and Pattern Recognition (CVPR), 2017, 2017	50204*	2017
A ConvNet for the 2020s Z Liu, H Mao, CY Wu, C Feichtenhofer, T Darrell, S Xie Computer Vision and Pattern Recognition (CVPR), 2022, 2022	6241	2022
Learning Efficient Convolutional Networks through Network Slimming Z Liu, J Li, Z Shen, G Huang, S Yan, C Zhang International Conference on Computer Vision (ICCV), 2017, 2017	3084	2017
Deep Networks with Stochastic Depth G Huang, Y Sun, Z Liu, D Sedra, KQ Weinberger European Conference on Computer Vision (ECCV), 2016, 2016	2833	2016
Rethinking the Value of Network Pruning Z Liu, M Sun, T Zhou, G Huang, T Darrell International Conference on Learning Representations (ICLR), 2019, 2019	1784	2019
Few-shot Object Detection via Feature Reweighting B Kang, Z Liu, X Wang, F Yu, J Feng, T Darrell International Conference on Computer Vision (ICCV), 2019, 2019	910	2019
DSOD: Learning Deeply Supervised Object Detectors from Scratch Z Shen, Z Liu, J Li, YG Jiang, Y Chen, X Xue International Conference on Computer Vision (ICCV), 2017, 2017	883*	2017
Test-time Training with Self-supervision for Generalization under Distribution Shifts Y Sun, X Wang, Z Liu, J Miller, A Efros, M Hardt International Conference on Machine Learning (ICML), 2020, 2020	854	2020
Imagebind: One Embedding Space to Bind Them All R Girdhar, A El-Nouby, Z Liu, M Singh, KV Alwala, A Joulin, I Misra* Computer Vision and Pattern Recognition (CVPR), 2023, 2023	761	2023
ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders S Woo, S Debnath, R Hu, X Chen, Z Liu, IS Kweon, S Xie Computer Vision and Pattern Recognition (CVPR), 2023, 2023	745*	2023
Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning Y Chen, Z Liu, H Xu, T Darrell, X Wang International Conference on Computer Vision (ICCV), 2021, 2021	703*	2021
A Simple and Effective Pruning Approach for Large Language Models M Sun, Z Liu, A Bair, JZ Kolter International Conference on Learning Representations (ICLR), 2024, 2024	358	2024
MSeg: A Composite Dataset for Multi-domain Semantic Segmentation J Lambert, Z Liu, O Sener, J Hayes, V Koltun Computer Vision and Pattern Recognition (CVPR), 2020, 2020	214	2020
Few Sample Knowledge Distillation for Efficient Network Compression T Li, J Li, Z Liu, C Zhang Computer Vision and Pattern Recognition (CVPR), 2020, 2020	183*	2020
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs S Tong, Z Liu, Y Zhai, Y Ma, Y LeCun, S Xie Computer Vision and Pattern Recognition (CVPR), 2024, 2024	172	2024
Un-mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning Z Shen, Z Liu, Z Liu, M Savvides, T Darrell, E Xing AAAI Conference on Artificial Intelligence (AAAI), 2022, 2022	133	2022
Regularization Matters in Policy Optimization--An Empirical Study on Continuous Control Z Liu, X Li, B Kang, T Darrell International Conference on Learning Representations (ICLR), 2021, 2021	90*	2021
Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space A Chavan, Z Shen, Z Liu, Z Liu, KT Cheng, E Xing Computer Vision and Pattern Recognition (CVPR), 2022, 2022	77	2022
One-for-all: Generalized LoRA for Parameter-Efficient Fine-Tuning A Chavan, Z Liu, D Gupta, E Xing, Z Shen arXiv preprint arXiv:2306.07967, 2023	70	2023
Dropout Reduces Underfitting Z Liu, Z Xu, J Jin, Z Shen, T Darrell International Conference on Machine Learning (ICML), 2023, 2023	51	2023

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